CVE-2026-105757
Last modified
CVE-2026-105757 is a medium-severity vulnerability rated 6.5/10 on the CVSS scale. vLLM is an inference and serving engine for large language models. Prior to 0.30.0, structured-output request failures can escape request-scoped validation and reach the EngineCore fatal-error path. EPSS estimates a 0.31% chance of exploitation in the next 30 days.
Description
vLLM is an inference and serving engine for large language models. Prior to 0.30.0, structured-output request failures can escape request-scoped validation and reach the EngineCore fatal-error path. A per-request backend mismatch can re-raise a grammar compilation exception, padding produced by the ngram_gpu speculative-decoding mode can pass a negative token to guidance validation, and the Rust frontend can admit empty structured-output values that the Python frontend rejects, allowing ordinary constrained-generation requests to terminate the shared engine. This issue is fixed in version 0.30.0.
Metrics
Weakness Enumeration
Affected Software
Source: CNA advisory (CVE.org). NVD analysis pending.
| Vendor | Product | Versions |
|---|---|---|
| vllm-project | vllm | < 0.30.0 |
References
Timeline
- Published
- Last Modified
- Status
- Awaiting Analysis
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